Abstract

Background

Twin data permit decomposition of comorbidity into genetically and
environmentally derived correlations. No previous twin study includes all
major forms of anxiety disorder.

Aims

To estimate the degree to which genetic and environmental risk factors are
shared rather than unique to dimensionally scored panic disorder, generalised
anxiety disorder, phobias, obsessive–compulsive disorder and
post-traumatic stress disorder.

Method

Data obtained from 2801 young-adult Norwegian twins by means of the
Composite International Diagnostic Interview were analysed with the Mx
program.

Results

A multivariate common factor model fitted best. The latent liability to all
anxiety disorders was substantially more heritable (54%) than the individual
disorders (23% to 40%). Most of the genetic effect was common to the
disorders. Genes contributed just over 50% to the covariance between
liabilities.

Conclusions

The five anxiety disorders all share genetic and environmental risk
factors. This has implications for the revision of the anxiety disorder
section in DSM–V.

Prior twin studies have consistently shown that genetic risk factors
contribute substantially to the aetiology of the five individual anxiety
disorders: panic disorder, generalised anxiety disorder (GAD), phobias,
obsessive–compulsive disorder (OCD) and post-traumatic stress disorder
(PTSD).1–8
As expected given the sharing of symptoms of anxiety across these disorders,
epidemiological studies have consistently shown substantial levels of
comorbidity.3,4,9–15
It is therefore of considerable interest to understand the sources of this
comorbidity. In particular, to what degree does it result from genetic
v. environmental risk factors common to all the anxiety disorders?
Although many twin studies have examined the relationship between anxiety
disorders and other disorders, for example GAD and major
depression,13–15
only two have examined solely anxiety
disorders.3,4
Neither study, however, included all five forms of anxiety disorder: one
examined panic disorder, GAD and
PTSD,3 whereas the
other examined panic disorder, GAD and four subtypes of
phobia.4 Our study
examines the structure of the genetic and environmental risk factors for all
the anxiety disorders assessed in an epidemiological sample of young-adult
Norwegian twins.

Method

Sample

Twins were ascertained for this study from the Norwegian Institute of
Public Health Twin Panel (NIPHTP), established in 1992. The twins were
identified through the Medical Birth Registry, established 1 January 1967,
which receives mandatory notification of all births in Norway. The first
NIPHTP questionnaire study was conducted in 1992. A follow-up study of all
Norwegian twins born 1967–79 was conducted in 1998. Altogether, 12 700
twins received the second questionnaire, and 8045 (63%) responded after one
reminder. The sample included 3334 complete pairs (53%). The NIPHTP is
described in detail
elsewhere.16

As an extension of the 1998 questionnaire study an interview study of Axis
I and Axis II mental health disorders – Mental Health in Twins (MHT) –
was started in 1999. All complete pairs from the questionnaire study
in which both twins had agreed to further contact (3153 pairs) were invited.
An additional 68 pairs were drawn directly from the NIPHTP sample. Altogether,
1391 pairs (43%) and 19 single twins were interviewed. There were valid
anxiety data for 1385 pairs – 219 male monozygotic (MZ), 117 male
dizygotic (DZ), 446 female MZ, 264 female DZ and 339 opposite-gender DZ –
and for 21 single twins. Age when interviewed was 19–36 years,
mean 28.1 years. Among non-participants was a small percentage of twin pairs
in which one or both twins could not be traced, and an unknown proportion for
whom migration, illness or other circumstances made participation impossible.
Informed consent was obtained from all participants after complete description
of the study. Zygosity was determined by molecular methods based on the
genotyping of 24 microsatellite markers in all but 385 pairs, for whom
zygosity was determined from questionnaire information. The estimated
misclassification rate in the entire sample, based on comparison between
questionnaire information and the results of DNA analysis, was 0.7%.

Measures

Axis I disorders according to DSM–IV were assessed using a
computerised version of the Composite International Diagnostic Interview
(CIDI).17,18
The interviews took place between June 1999 and May 2004 and were conducted
face to face except for 231 telephone interviews (8.3%). The majority of the
28 interviewers were psychology students in their final training or
experienced psychiatric nurses. All received a standardised training programme
by teachers certified by the World Health Organization and passed a user
licence test for the CIDI. They were supervised during the data collection
period. Each twin in a pair was interviewed by different interviewers masked
to the results of the co-twin.

For the five lifetime anxiety disorders (including subthreshold scores)
here examined (panic disorder, GAD, phobias, OCD and PTSD), DSM–IV
diagnoses were assigned without hierarchical rules. Preliminary analyses
indicated that the prevalence rates for the full diagnostic categories for
four of the diagnoses (panic disorder, GAD, OCD and PTSD) were not high enough
to produce stable estimates for twin modelling with our sample size. Moreover,
the limited prevalence rates required the collapsing of agoraphobia, social
phobia and the other forms of phobias. Using empirically validated methods,
detailed below, we therefore defined subthreshold diagnostic groups. Full
anxiety disorders were scored ‘2’, subthreshold anxiety disorders
were scored ‘1’ and the remainder of the sample was scored ‘
0’.

Criteria for defining subthreshold cases

The process of generating subthreshold data took place in two steps.
Initially we used only data from the CIDI interview as criteria. However,
preliminary standard error of the mean (s.e.m.) testing showed that not even a
careful relaxation based on the single CIDI items gave sufficiently high
subthreshold prevalences for three of the variables to arrive at stable
analytic solutions. As a second step it was therefore decided to extend the
subthreshold groups using available questionnaire data as criteria as
well.

CIDI-based criteria

Several possible combinations of endorsed interview items, judged to
reflect the essential symptoms of the disorder but representing a lower
symptom level than the full diagnosis, were tried for all of the disorders
except phobias. As a crude empirical tool for selecting some of these
combinations we used mental health scores from a questionnaire. A study from
1998 of the twins later invited to participate in the study reported here,
included a five-item abbreviated version of the global Symptom Checklist
SCL–25. This short version (SCL–5) has been shown to correlate at
0.92 with the original
instrument,19 and
correlates substantially with all the CIDI-based anxiety disorders.

A number of alternative combinations of subthreshold criteria were tested
for each of the disorders, comparing mean SCL–5 scores between the
groups of cases meeting the various sets of criteria. Comparisons of
SCL–5 scores were also made between cases with a full diagnosis, groups
with symptoms meeting the various subthreshold definitions, and the remaining
sample. As a precondition for a set of subthreshold criteria to be chosen, the
cases meeting these criteria were required to have mean SCL–5 scores
lower than those from the full diagnosis group and higher than those from the
remaining sample. More than one combination of subthreshold criteria was
sometimes chosen for the same disorder; for instance, alternative relaxations
would be either a reduction of the required number of symptoms or a reduction
of the required duration of the period experiencing these symptoms. The degree
of relaxation for the various alternatives was balanced by comparing the
SCL–5 mean scores for the groups of participants meeting each of the
alternative criteria. The set of CIDI-based subthreshold criteria, initially
selected according to clinical judgement and empirically shown to be
associated with poor general mental health, is given in the Appendix.

No subthreshold group was defined for phobias, which were highly prevalent.
However, like the other disorders, phobia was trichotomised. Mean SCL–5
scores were much lower for participants with phobias (0.39 higher than healthy
participants) than for participants with any other anxiety disorder (1.10 s.d.
higher than healthy participants). Participants with two or more phobic
disorders scored 0.72 s.d. higher. These results imply that most people with a
single phobia are not severely mentally ill. Thus, rather than relaxing the
criteria for the already prevalent phobia scores, the criterion for the top
phobia score (2) was restricted to ‘two or more types of phobia
diagnoses’. A single phobia diagnosis was scored 1. The mean SCL–5
score of subthreshold scorers for any anxiety disorder diagnosis or people
with one full phobia disorder was 0.45 s.d. higher than that of healthy
participants.

Extending the subthreshold groups using questionnaire items

Included in the 1998 questionnaire were questions about symptoms of panic
disorder and OCD, enquiring both about the situation at the time of the study
and about symptoms earlier in life, and seven items tapping GAD-related
symptoms. Logistic regression analysis was used to select combinations of
questionnaire items that best predicted the full CIDI-based panic disorder and
OCD diagnoses. For panic disorder the single item ‘Can suddenly get
extremely afraid or panic without a reason’, endorsed for either ‘
now’ or ‘earlier in life’, was found to best predict
a panic disorder diagnosis. The tetrachoric correlation between this
questionnaire score and a full DSM panic disorder diagnosis was 0.68. The
frequency of participants reporting panic-like spells, now or earlier in life,
was 6.5%.

From three items made to tap OCD symptoms, the combination of two items, ‘
I check and inspect too often, for instance electric burners and locked
doors’ (‘now’) and ‘I’m often bothered by “
stupid” ideas, which keep coming back’ (‘now’
or ‘earlier’), best predicted OCD diagnosis. The tetrachoric
correlation between having endorsed both these items and OCD diagnosis was
0.46. The frequency of positive questionnaire scores was 6.1%.

Linear regression analysis was used to select questionnaire items that best
predicted GAD, scored as an ordinal variable. A sum of seven items, weighted
according to the result from the regression analysis, was computed. The items
from SCL–5 were [Have, during the past 14 days, been bothered by] ‘
feeling fearful’, ‘feeling tense or keyed up’ and ‘
worrying too much about things’. Other questionnaire items were: ‘
How often, during the past month, have you used
sedatives/tranquillisers?’ ‘Have you, during the last month, been
bothered by nervousness (irritable, agitated, tense or restless)?’ ‘
Do you on the whole feel energetic and fit or tired and worn
out?’ ‘Have you, during the past month, had problems with sleeping
in or other sleep problems?’ The upper 7.5% were scored as subthreshold
GAD if not already having a GAD diagnosis. The tetrachoric correlation between
this dichotomised questionnaire-based indicator and GAD diagnosis was 0.56.
The correlation between this indicator and the other full anxiety disorders
varied from 0.34 to 0.51.

No questionnaire data were available to predict PTSD.

Statistical analysis

The phenotypic correlation structure was examined using confirmatory factor
analysis. First, we tested whether the structure could be explained by a
single factor. Then possible gender differences were explored by constraining
the anxiety disorder factor loadings to be equal in men and women. Finally, we
explored whether adding subthreshold cases might have changed the multivariate
structure of the disorders by comparing results using trichotomous (including
subthreshold scores) and dichotomous (full or no diagnosis) data. Model fit is
assessed by the root mean squared error of approximation (RMSEA) where
good-fitting models have a value under
0.05.20

Our twin modelling assumed that liability to illness is continuous and
normally distributed in the population, with individuals who exceed a first
theoretical threshold expressing a subsyndromal form, and those who exceed a
higher threshold expressing the full disorder. Resemblance in twin pairs is
assessed using a polychoric
correlation.21
Using the multiple threshold model in the PRELIS
program,22 we
tested for deviations from an underlying bivariate normal distribution of the
ordinal three-category data. This test was used for examining whether the
subthreshold and fully syndromal cases reflect quantitatively different levels
of liability on the same underlying dimension.

Individual differences in liability are assumed to arise from three
sources: additive genetic ‘A’, from genes whose allelic
effects combine additively; common environment ‘C’, which
includes all sources similarly influencing both twins; and specific
environment ‘E’, which includes environmental experiences
not shared by co-twins and measurement error. Monozygotic co-twin similarity
is due to identical genes, A, and, by definition, common environment,
C. Dizygotic pairs share (on average) half of their A and
all of their C.

Univariate twin studies use data on co-twin similarity for a single trait
or illness. Multivariate studies use observed similarity between the same
trait in co-twins, between one trait in one twin and another trait in the
co-twin, and between the various traits observed within individuals. Besides
yielding estimates of A, C and E for individual disorders,
multivariate analyses estimate the extent to which variation in comorbid
disorders results from the same genetic or environmental factors v.
genetic and environmental factors specific to each disorder.

We used single-factor multivariate models because these served our purpose
of dividing genetic and environmental variance into that shared between
anxiety disorders and that specific to each disorder. We tested two forms of
this model: an independent pathway and a common pathway
model.23 The latter
is nested under the former and differs in that all common variance, genetic
and environmental, is assumed to be mediated through one single latent
phenotype. The best-fitting of these two models was chosen using
Akaike’s information criterion
(AIC).24

Ideally, quantitative and qualitative gender-specific effects would be
tested as part of our multivariate modelling. This was not feasible with these
data because multivariate analyses are especially vulnerable to the
combination of low prevalences and modest sample size (especially in our male
DZ pairs). For some of the sets of disorders we could not find any pair with
two affected twins (e.g. PTSD in one twin and OCD in the other). Such empty
cells destabilised solutions. We therefore evaluated gender-specific effects
for one disorder at a time, assuming that we could ignore such effects in
multivariate models unless they were robustly detected across single
disorders. Briefly, no evidence for any qualitative gender effect (which
allows for gender-specific sources of genetic or environmental effects) or
quantitative gender effect (which permits differing estimates of genetic and
environmental effects by gender) was found for panic disorder, GAD or OCD.
Modelling indicated some support for qualitative gender effects for phobia and
quantitative gender effects for PTSD. In the light of these modest and
inconsistent findings, we excluded gender effects from our multivariate
modelling.

Twin models are often simplified by dropping insignificant paths. However,
Sullivan & Eaves have shown that in the presence of low power – as
is the case in these analyses – full models may better approximate
reality than do simpler best-fit
models.25 This is
because, with low power, the effects originally distributed among several
parameters may be aggregated into a few inflated parameters with
unrealistically small confidence intervals. With the limited power of our
data, we present results from the full best-fitting multivariate model with no
attempt at further simplification. The Mx computer program was used for the
analyses.26 Raw
data analysis was applied and the thresholds (prevalences) were permitted to
vary between men and women.

Results

Prevalence and phenotypic correlational structure

The prevalence estimates for the full and subthreshold definitions of panic
disorder, GAD, phobia, OCD and PTSD are shown in
Table 1. The phenotypic
polychoric correlations between these disorders are presented in
Table 2. Most vary between 0.35
and 0.55. In both men and women, panic disorder and GAD were the most strongly
and OCD and PTSD the least strongly inter-correlated disorders. By
confirmatory factor analysis, a single-factor solution allowing estimates to
differ across genders fitted the data very well
(χ210 = 6.86, P = 0.739, RMSEA = 0.000).
Factor loadings were similar across genders except for a lower loading for OCD
in women (Table 2).
Constraining the factor loadings to equality in men and women hardly worsened
the fit (χ215 = 11.66, P = 0.705, RMSEA =
0.000). We performed the same analysis on our dichotomous data eliminating
subthreshold cases. The results were similar to those seen including the
subthreshold cases (Table
2).

Phenotypic correlations between five anxiety disorders and loadings from a
single-factor confirmatory factor analysis

Testing the assumption of a single dimension of liability

To examine further whether full-criteria and subthreshold diagnoses
reflected the same underlying liability, we applied the multiple threshold
model to all bivariate combinations – within individuals, between twins
within disorder, and cross-twin cross-disorder – testing 45
relationships in each of five zygosity groups. The mean probability value for
these 225 tests was 0.43, close to 0.50 expected; 7.6% of the values exceeded
0.05, close to chance expectations.

Multivariate model fitting and results

The common pathway model provided a better fit to the data than the
independent pathway model (Δχ27 = 11.60,
P = 0.11, ΔAIC = –2.40). The results for the
full common pathway model are shown in Fig.
1, where squaring the path coefficients gives the proportions of
variance explained. The latent phenotypic factor – a general liability
to all anxiety disorders – is substantially influenced by genetic
factors, with an estimated heritability of 54%. In contrast, the contribution
of shared environment was small (6%) and not statistically significant.
Individual-specific environment equalled 40%.

The paths from the common factor to the individual disorders closely mirror
those found in the confirmatory factor analysis
(Table 2), with highest
loadings seen for panic disorder and GAD scores and lowest loadings for OCD
and PTSD scores. The genetic and environmental effects specific to each
anxiety disorder score are seen in the lower part of
Fig. 1. Disorder-specific
genetic effects are negligible for panic disorder and GAD, intermediate but
non-significant for OCD and PTSD and strongest for phobia. A more informative
way to interpret these results is seen in
Table 3, which presents
estimated total heritability and the percentage of genetic effects for each
disorder score resulting from the common factor and unique to each disorder
score. Total heritabilities were generally modest, ranging from 23% for PTSD
to 40% for phobias. The proportions of genetic effects unique to each disorder
score were more variable, ranging from 4% for GAD to 40% for phobia and 45%
for OCD.

Magnitude and origin of genetic, shared environmental and
individual-specific environmental effects for five anxiety disorders from the
best-fit common factor model

The estimated shared environmental effects specific to each disorder score
were modest and none reached significance. They vary, being estimated at zero
for panic disorder and phobia scores, and to account for 8% of total variance
in liability for GAD scores and 10% for OCD scores. As seen in
Table 3, for three of the
anxiety disorder scores – GAD, OCD and PTSD – most of the shared
environmental effects appeared to be disorder-specific. For the remaining two
disorder scores – panic disorder and phobia – the very modest
shared environmental effects were entirely common to all disorders. Non-shared
environment contributed to the comorbidity with about two-thirds of the
genetic contribution.

Discussion

Our analyses had four noteworthy results. First, in an epidemiological
sample of young-adult twins, confirmatory factor analysis found that a single
factor could well explain the observed comorbidity between lifetime diagnoses
of the five forms of anxiety disorder (including subthreshold scores), both
when diagnosed using traditional DSM–IV criteria and when including
empirically derived subthreshold cases. Loadings on this common factor were
strongest for panic disorder and GAD and weakest for OCD and PTSD. Second, a
common pathway multivariate twin model fitted the data well. The latent
liability common to all anxiety disorder scores was substantially heritable
(54%) with only a minimal and non-significant estimated contribution from the
shared environment. Third, the total heritability of the five anxiety disorder
scores was generally moderate and ranged from 23% for PTSD to 40% for phobia.
Fourth, the pattern of disorder-specific loadings for the five individual
disorder scores was variable and informative. All five anxiety disorder scores
derived the majority of their genetic risk from the common factor. Panic
disorder and GAD had minimal disorder-specific genetic effects, indicating
that these two disorders best indexed the genetic liability common to all
anxiety disorder scores. In contrast, OCD derived almost half its genetic
effect from factors specific to that disorder score. Although modest in
overall magnitude, for three of the variables – GAD, OCD and PTSD –
the majority of the shared environmental influences seemed to be
disorder-specific in nature.

Interpretation and comparison with prior results

Epidemiological studies from New
Zealand,9 the
USA,10
Australia11 and
Holland12 have all
shown correlations and factor loadings for the anxiety disorders that
correspond well with our results. Our heritability estimates for panic
disorder, GAD, phobia and OCD are similar to or slightly lower than those
previously
reported.1–8
A meta-analysis of previous twin studies estimated heritabilities of 0.43 for
panic disorder, 0.32 for generalised anxiety disorder and 0.20–0.37 for
various types of
phobias.2 A review
of twin studies on obsessive–compulsive disorders reported
heritabilities of 0.27 to
0.47.8 Analyses of
the only large twin sample with PTSD data, the Vietnam Era Twin Registry, have
shown a heritability of
0.35,3 compared with
our estimate of 0.23. Our results may be lower because the rates of severe
trauma – a prerequisite for a PTSD diagnosis – were probably much
lower in our community sample than in a cohort of male war veterans. This
would be likely to reduce heritability, since our sample would contain
individuals at high genetic risk of PTSD that would not be manifested owing to
the absence of trauma exposure.

Our multivariate findings can be usefully compared with those from the two
most comparable prior studies. Chantarujikapong et al found that a
single-factor independent pathway model best fitted lifetime PTSD and symptoms
of GAD and panic disorder in 3371 male pairs from the Vietnam Era Twin
Registry.3 Their
results agreed with ours in finding nearly all genetic effects on GAD to be
shared with the other anxiety disorders and approximately a third of the
genetic risk of PTSD to be disorder-specific. Their results differed, however,
in finding a much higher proportion of genetic effects on panic disorder to be
disorder-specific (49% in their study v. 9% in ours). Hettema et
al analysed data on panic disorder, GAD, agoraphobia and social, animal
and situational phobias in approximately 5000 twins in the
USA.4 Their results
differed from ours in suggesting that two genetic factors were required to
explain the observed patterns of comorbidity. Their results concurred with
ours in finding that GAD and panic disorder shared nearly all genetic risk
factors whereas at least some subtypes of phobias were strongly influenced by
genetic factors only weakly related to panic disorder and GAD.

A notable result from our model fitting is the higher heritability for the
common anxiety disorder factor than for any of the individual disorders. This
is, however, not unexpected from a psychometric perspective. Unreliability of
measurement, which is a concern for some anxiety disorders, especially when
assessed in non-clinical
populations,27–29
will more substantially attenuate the heritability of the individual disorders
than the latent common factor.

Implications for DSM–V

These results have four implications for those pondering the structure of
anxiety disorders in the fifth edition of the DSM. First, despite strong
evidence that GAD and major depressive disorder are genetically closely
related,13–15
our results suggest that GAD is also strongly related genetically to the other
anxiety disorders. Thus, genetic findings alone cannot justify its removal
from the anxiety disorders and placement within the mood disorders. The
genetic relationship between major depression and GAD may be non-specific and
indicative of a broad shared genetic liability across a wide range of
internalising
disorders.30
Second, our results provide some support for the aetiological coherence of the
anxiety disorders. All five dimensionally scored disorders do have appreciable
loadings on the common factor. However, third, OCD and PTSD do differ from the
other three anxiety disorders in that they have the lowest loadings on the
common factor, and appear to have appreciable disorder-specific genetic
and shared environmental influences. Thus, these two disorders in our
data are the least closely related to the common factor. Fourth, the results
for phobias are somewhat anomalous: on the one hand this disorder has a
relatively high loading on the common factor, but on the other it has the
greatest disorder-specific genetic risk factors. This might be the result of
combining the different phobias, which may have partially distinct genetic and
environmental risk factors as suggested by prior
findings.4,31,32
However, we also cannot exclude the possibility that our deviating findings
for phobia to some extent reflect our choice of a common pathway model, which
in terms of AIC value was only marginally favourable to the independent
pathway model. The latter, on which previous estimates were based, produced
somewhat different results.

Limitations

These results should be interpreted in the context of eight potential
methodological limitations. Our sample consisted of young-adult Norwegian
twins, and these results may not generalise to other populations. Despite our
substantial sample size, limited prevalence for all the anxiety disorders
except phobias required that we use subthreshold cases to permit meaningful
model fitting. These cases were empirically defined, and for three variables
where questionnaire data were used to extend the subthreshold groups, the
questionnaire data correlated moderately to highly with the diagnostic data.
Their addition did not appreciably alter the results of confirmatory factor
analysis. Multiple threshold analyses showed that they reflected the same
liability dimensions as the syndromal DSM–IV cases. However, our results
might still have differed somewhat if based on DSM-defined disorders only.

As detailed
elsewhere,33 only
pairs who had participated in a previous questionnaire study were invited to
the MHT study. Thus, considerable attrition, taking place in two steps, might
imply recruitment bias of the results. However, unpublished results have shown
only a moderate selection towards superior mental health in previously
completed questionnaires. Biometric genetic analyses of mental health
variables from the questionnaires did not differ between MHT participants and
non-participants. Accordingly, substantial recruitment bias of the biometric
genetic analyses in this study is unlikely. Univariate analyses suggested that
there could be quantitative and qualitative gender differences for phobias and
PTSD that we were unable to incorporate into our multivariate model.
Therefore, results for these variables should be interpreted as an approximate
average across genders rather than fully valid for men and women specifically.
Qualitative gender-specific effects if ignored will bias the estimates of
heritability upwards. However, most of the heritability estimates for our
modelling were somewhat lower than expected from previous results. It is
unlikely that our results were substantially biased by our inability to model
gender effects.

Phobia subtypes may be partly influenced by different
genes.4,31,32
Results from a twin study suggest a particularly strong familial covariance
between agoraphobia and panic
anxiety.34 Given
low rates of certain subtypes, especially in our male participants, we could
not include phobia subtypes in our multivariate models. Therefore, our results
for phobias are inevitably averaged across the subtypes.

Because our analyses included only anxiety disorders, they cannot address
the important question of whether the genetic and environmental risk factors
common to all anxiety disorders are specific only to anxiety disorders or
shared with other internalising disorders. The specification of genetic or
environmental effects common to two or more phenotypes does not exclude the
possibility of causal relationships between these phenotypes. If phenotype
X causes phenotype Y, genetic or environmental factors
primarily affecting X will be mediated through X and
indirectly affect Y. Our twin modelling and data are not informative
on possible causal relationships between the anxiety disorders. Such causal
relationship will only be expressed as genetic or environmental variance
common to the disorders.

Finally, the observed genetic covariance structure as well as the
diagnosis-specific genetic variance might perhaps be further decomposed into
effects of genes coding for possible endophenotypes. The latter are by
definition more fundamental and genetically more homogeneous than complex
phenotypes such as anxiety disorders. Possible endophenotypes might include
behavioural characteristics such as ‘behavioural
inhibition’,35
biological factors such as gamma-aminobutyric acid type A receptor
diversity,36 or
perhaps a combination of the two such as sensitivity to
hypercapnia.37
Although our study, not informative on such factors, first and foremost needs
replication based on diagnostic data, future twin studies of diagnostic
anxiety data together with endophenotypic data may further extend our
understanding of the comorbidity among anxiety disorders.

Funding

This study was supported by
NIH grants
MH-068643 (principal investigator K.S.K.) and
MH-65322 (principal investigator M.C.N.). The twin
programme of research at the Norwegian Institute of Public Health is supported
by grants from the Norwegian Research Council,
the Norwegian Foundation for Health and
Rehabilitation, the Foundation of Borderline
Research, and the European
Commission under the programme Quality of Life
and Management of the Living Resources of the Fifth Framework
Programme (number QLG2-CT-2002-01254).
Genotyping of the twins was performed at the Starr Genotyping Resource Centre
at Rockefeller University.

Appendix

Subthreshold criteria

Panic disorder

Meeting criteria for panic attack.

OR

Confirming ‘ever had an attack when all of a sudden you felt
frightened, anxious or very uneasy? Some people call it a panic attack’
without being in danger, AND endorsing four or more of the 17 types of
symptoms listed in the interview.

Generalised anxiety disorder

Two of the six DSM criteria were relaxed in various ways.

(i) (A) Felt worried, tense or anxious over longer than 3 months
(originally 6 months); worried 2–3 days a week (originally ≥4 days);
worried about everyday events, but did not perceive the worrying to be ‘
excessive, that is, stronger than in other people in similar
situation’ (originally required to be ‘excessive’).

(E) Anxiety interfered at least ‘somewhat’ (originally at least ‘
a lot’) with life/daily activities; reported at least three of
seven types of symptoms (originally in DSM–IV, three of six types of
listed symptoms are required. An extra type of symptom, ‘feels like
having a lump in one’s throat’ is added in the CIDI).

OR

(ii) As (i), except (A): the period lasted 6 months, and (E): only two
types of symptoms were required.

OR

(iii) As (i), except (A): worrying was also perceived by the individual to
be excessive and (E): only two types of symptoms were required.

Obsessive–compulsive disorder

Endorsing any of the CIDI OCD screening questions about clearly obsessive
or compulsive symptoms.